TITLE:
Structural Limitations of Push Inventory Management Systems in High Environmental Variability Conditions
AUTHORS:
Sviatoslav Oliinyk
KEYWORDS:
Inventory Management, Push Systems, Demand Variability, Safety Stock, Bullwhip Effect, Distribution Architecture
JOURNAL NAME:
American Journal of Industrial and Business Management,
Vol.16 No.3,
March
19,
2026
ABSTRACT: The article examines the structural limitations of push-type inventory management systems as an integral property of decision architecture under conditions of high environmental variability, stochastic lead times, and fragmented distribution networks. The analysis is based on a comparative review of contemporary studies addressing safety stocks, the bullwhip effect, buffer parameterization, production–inventory planning, and warehouse centralization strategies. It is shown that isolated optimization of order quantity or service level does not ensure system stability and leads to reproducible trade-offs between holding costs, stockout probability, and flow throughput. The study argues that the primary source of instability lies in the forecast-centric decision sequence “inventory-production-distribution,” which amplifies sensitivity to demand dispersion and temporal deviations. It is demonstrated that increasing safety stocks performs a function of local fluctuation compensation while simultaneously scaling systemic imbalances when misaligned with production capacities and replenishment lead times. Particular attention is given to distribution architecture and the risk-pooling effect, indicating that centralization reduces variability amplitude without eliminating its forecast-driven nature, whereas signal-buffer and pull logics enhance flow adaptability but do not guarantee the removal of structural constraints. It is shown that managerial stability is determined by the coherence of informational, resource, and spatial contours rather than by the precision of individual parameters. The article may be useful for researchers of logistics systems, supply chain management professionals, and developers of inventory planning models under uncertainty.